Eye state detecting method and eye state detecting system

ABSTRACT

An eye state detecting method, which comprises: (a) capturing a detecting image; (b) computing a brightness variation tendency for a peripheral part of a darkest part of the detecting image; and (c) determining whether a user&#39;s eye is in an opening state or in a closing state according to the brightness variation tendency

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of applicant's earlier application,Ser. No. 15/199,965, filed Jun. 30, 2016 and is included herein byreference.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to an eye state detecting method and aneye state detecting system, and particularly relates to an eye statedetecting method and an eye state detecting system which can determinean eye state via an image with a low resolution and a smallerdetermining range.

2. Description of the Prior Art

More and more electronic apparatuses have the function for detecting aneye opening state or an eye closing state. Such functions can remind theuser his eye is close, to avoid the user's eye closes at an impropertiming (ex. while taking a picture). Also, the user can accordinglycontrol the electronic apparatus via opening eyes or closing eyes. Suchelectronic apparatus needs a detecting apparatus to detect the eyeopening and the eye closing. One of the detecting methods is capturingimages via an image sensor, and detecting whether the user opens his eyeor closes his eye based on features of images.

However, images with high resolutions or larger determining ranges areneeded if a proper determination for features of images is desired, thusthe cost for the electronic apparatus rises, or more computing loadingis needed, which causes higher power consumption. However, it is hard toidentify the features of images if images with low resolutions areapplied for detecting, thus it is hard to detect whether the user openhis eye or close his eye.

SUMMARY OF THE INVENTION

One objective of the present invention is to provide a detecting methodthat can use an image with a low resolution to determine the eye state.

Another objective of the present invention is to provide a detectingsystem that can use an image with a low resolution to determine the eyestate.

One embodiment of the present invention discloses an eye state detectingmethod, which comprises: (a) capturing a detecting image; (b) computinga brightness variation tendency for a peripheral part of a darkest partof the detecting image; and (c) determining whether a user's eye is inan opening state or in a closing state according to the brightnessvariation tendency.

Another embodiment of the present invention discloses an eye statedetecting system, which comprises: a control circuit; an image sensor,wherein the control circuit controls the image sensor to capture adetecting image via a detecting range; and a computing circuit,configured to compute a brightness variation tendency for a peripheralpart of a darkest part of the detecting image, and to determine whetherthe user's eye is in an opening state or in a closing state according tothe brightness variation tendency.

Still another embodiment of the present invention discloses an eye statedetecting method, applied to an electronic apparatus with an imagesensor, which comprises: (a) acquiring a detecting image via the imagesensor; (b) defining a face range on the detecting image; (c) defining adetermining range on the face range; and (d) determining if thedetermining range comprises an open eye image or a close eye image.

Still another embodiment of the present invention discloses an eye statedetecting system, comprising: a control circuit; an image sensor,wherein the control circuit controls the image sensor to capture adetecting range; and a computing circuit, configured to define a facerange on the detecting image, to define a determining range on the facerange, and to determine if the determining range comprises an open eyeimage or a close eye image.

In view of above-mentioned embodiments, the eye state for the user canbe determined without detail image features and without an image havinga large range, thus the issue for prior art that an image with a highresolution is needed for determining the eye state for the user and highpower consumption due to large computing loading can be solved.

These and other objectives of the present invention will no doubt becomeobvious to those of ordinary skill in the art after reading thefollowing detailed description of the preferred embodiment that isillustrated in the various figures and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram illustrating an eye state detecting methodaccording to one embodiment of the present invention.

FIG. 2 is a schematic diagram illustrating that a smart glass appliesthe eye state detecting method in FIG. 1.

FIG. 3 is a schematic diagram illustrating the comparison between thebrightness variation caused by the eye state detecting methodillustrated in FIG. 1 and the brightness variation for prior art.

FIG. 4 is a flow chart illustrating an eye state detecting methodaccording to one embodiment of the present invention.

FIG. 5 is a schematic diagram illustrating an eye state detecting methodaccording to another embodiment of the present invention.

FIG. 6 is a flow chart illustrating the eye state detecting methoddepicted in FIG. 5.

FIG. 7 is a block diagram illustrating an image detecting apparatusaccording to one embodiment of the present invention.

FIG. 8 is a schematic diagram illustrating an eye state detecting methodaccording to another embodiment of the present invention.

FIG. 9 is a schematic diagram illustrating detail steps for theembodiment illustrated in FIG. 8.

FIG. 10 is a flow chart illustrating an eye state detecting methodprovided by the present invention.

DETAILED DESCRIPTION

In following descriptions, several embodiments are provided to explainthe concept of the present invention. Please note, the devices infollowing embodiments, for example, the unit, the module or the system,can be implemented by hardware (ex. a circuit) or hardware with firmware (ex. programs written to a microprocessor).

FIG. 1 is a schematic diagram illustrating an eye state detecting methodaccording to one embodiment of the present invention. As illustrated inFIG. 1, the eye detecting method provided by the present inventionapplies a detecting range DR to capture a detecting image, anddetermines whether the user's eye is in an opening state or in a closingstate according a brightness of to the detecting image. In oneembodiment, an average brightness is applied to determine whether theuser's eye is in the opening state or in the closing state. The averagebrightness is low if the user opens his eye, since the detecting imagecomprises an image of an eye. On the contrary, the average brightness ishigh if the user closes his eye, since a large part of the detectingimage is an image of skin. Accordingly, the average brightness can beapplied to determine whether the user's eye is in the opening state orin the closing state.

In this embodiment, the detecting range DR is smaller than a maximumdetecting range MDR, and the location thereof is pre-defined. In oneembodiment, the possible location for the user's eye is pre-defined, andthe detecting range DR is decided based on the possible location. FIG. 2is a schematic diagram illustrating that a smart glass applies the eyestate detecting method in FIG. 1. Take FIG. 2 for example, the maximumdetecting range MDR is a range that the glass contains. The eyes of theuser always locate a central location if the user wears a smart glass,thus the central location can be applied as a basement to determine thedetecting range DR. However, please note the embodiment illustrated inFIG. 1 is not limited to be applied to the smart glass illustrated inFIG. 2. The embodiment illustrated in FIG. 1 can be applied to otherapparatuses, for example, a wearable apparatus for head, a displayapparatus with a camera or a portable apparatus.

In the embodiment of FIG. 1, if the maximum detecting range MDR isapplied to capture the detecting image rather than the detecting rangeDR, the computing data amount becomes large. Also, in such case theimage for the eye only occupies a small part of the whole detectingimage while the user opens his eye, thus the average brightness thereofis similar with the average brightness for the detecting image while theuser closes his eye. Thereby it is hard to determine whether the useropens or closes his eye. As illustrated in FIG. 3, if the maximumdetecting range MDR is applied to capture the detecting image, theaverage brightness for the detecting image while the user opens his eyeand the average brightness for the detecting image while the user closeshis eye are similar. On the opposite, if the detecting range DR smallerthan the maximum detecting range MDR is applied, the average brightnessfor the detecting image while the user opens his eye and the averagebrightness for the detecting image while the user closes his eye havemore significant difference.

FIG. 4 is a flow chart illustrating an eye state detecting methodaccording to one embodiment of the present invention, which comprisesfollowing steps:

Step 401

Decide a detecting range according to a possible location of a user'seye. Take FIG. 2 for example, the user's eye may locate at a centrallocation of a smart glass, thus the detecting range is decided based onthe central location.

Step 403

Capture a detecting image via the detecting range of the step 401.

Step 405

Determine whether the user's eye is in an opening state or in a closingstate according a brightness of to the detecting image.

Another embodiment of the present invention is disclosed as below, whichdetermines whether the user's eye is in an opening state or in a closingstate according a brightness variation tendency. One of the determiningrule is: the darkest part for the image is always one part of the eyewhile the user opens his eye and the peripheral region for the darkestpart is also one part of the eye, thus has a dark image as well.Accordingly, the brightness variation tendency for the peripheral regionof the darkest part is gentle while the user opens his eye. On theopposite, the darkest part for the image is always a region that is notskin (ex. the eyelash) while the user closes his eye and the peripheralregion for the darkest part is skin in such case. Accordingly, theperipheral region for the darkest part in this case has a brighterimage. Therefore, the brightness variation tendency for the peripheralregion of the darkest part is sharp while the user closes his eye.Please note, the following embodiments can be implemented with theembodiment illustrated in FIG. 1 to FIG. 4, that is, the smallerdetecting range is applied to capture the detecting image.

FIG. 5 is a schematic diagram illustrating an eye state detecting methodaccording to another embodiment of the present invention. In suchembodiment, the brightness for each image row of the detecting image issummed and the image row with a lowest brightness is found. Take FIG. 5for example, the image row with a lowest brightness is the seventh rowwhile the user opens his eye and the image row with a lowest brightnessis the twelfth row while the user closes his eye. According to FIG. 5,the variation for the sum of each image row's brightness is gentle whilethe user opens his eye. On the contrary, the variation for the sum ofeach image row's brightness is sharp while the user closes his eye. Manymethods can be applied to acquire the brightness variation tendency. Inone embodiment, the image row with a lowest brightness is selected asthe standard image row, and a brightness sum difference between thebrightness sum of the standard image line and brightness sums for atleast two of the image lines are acquired. After that, the brightnessvariation tendency is decided according to the brightness sumdifference.

In one embodiment, the standard image line is an N-th image line of thedetecting image. In such case, brightness sum differences between thebrightness sum of the standard image line and brightness sums for eachone of image lines from an N+1-th image line to an N+K-th image line ofthe detecting image are computed. Furthermore, the brightness sumdifferences between the brightness sum of the standard image line andbrightness sums for each one of image lines from an N−1-th image line toan N−K-th image line of the detecting image are computed. The K is apositive integer larger or equaling to 1.

Such embodiment will be explained via an example as below:

TABLE 1 Eye Open Eye Close a9 4035 4188 a10 3514 4258 a11 2813 4311 a122542 4035 a13 2669 3772 a14 2645 3226 a15 2835 2703 a16 3154 2643 a173564 2878 a18 3888 3365 a19 4142 3745

Table 1 illustrates brightness sums for different pixel rows while aneye is open and while an eye is close. The ax indicates the brightnesssum for the x-th pixel row. For example, a9 indicates the brightness sumfor the 9-th pixel row, and a15 indicates the brightness sum for the15-th pixel row. In such example, the pixel row with a lowest brightnesswhile the eye is open is the 12-th row, which has a brightness sum of2542 (a12). If the above-mentioned K is 3, brightness sum differencesbetween the brightness sum of the 12-th image row and brightness sumsfor each one of image rows from a 9-th image row to an 11-th image rowof the detecting image are computed. Also, brightness sum differencesbetween the brightness sum of the 12-th image row and brightness sumsfor each one of image rows from a 13-th image row to a 15-th image rowof the detecting image are computed. Such operations are depicted in theEquation (1):

Equation (1): Eye Open

Brightness sumdifference=(a9−a12)+(a10−a12)+(a11−a12)+(a13−a12)+(a14−a12)+(a15−a12)

Similarly, the pixel row with a lowest brightness while the eye is closeis the 16-th row, which has a brightness sum of 2643 (a16). If theabove-mentioned K is 3, brightness sum differences between thebrightness sum of the 16-th image row and brightness sums for each oneof image rows from a 13-th image row to a 15-th image row of thedetecting image are computed. Also, brightness sum differences betweenthe brightness sum of the 12-th image row and brightness sums for eachone of image rows from a 17-th image row to a 19-th image row of thedetecting image are computed. Such operations are depicted in theEquation (2):

Equation (2): Eye Close

Brightness sumdifference=(a13−a16)+(a14−a16)+(a15−a16)+(a17−a16)+(a18−a16)+(a19−a16)

Based on Equation (1), the brightness sum difference while the eye isopen is: (4035−2542)+(3514−2542)+(2813−2542)+(2669−2542)+(2645−2542)+(2835−2542)=3259.

Based on Equation (2), the brightness sum difference while the eye isclose is: (3772−2643)+(3226−2643)+(2703−2643)+(2878−2643)+(3365−2643)+(3745−2643)=3831

The above-mentioned Equation (1) and Equation (2) can be regarded as acost function. New cost functions can be acquired if the concept ofabsolute values is added to Equation (1) and (2), thereby Equation (3)and (4) are acquired.

Equation (3): Eye Open

Brightness sumdifference=|a9−a10|+|a10−a11|+|a11−a12|+|a13−a12|+|a14−a13|+|a15−a14|

Equation (4): Eye Close

Brightness sumdifference=|a13−a14|+|a14−a15|+|a15−a16|+|a17−a16|+|a18−a17|+|a19−a18|

Based on Equation (3), the brightness sum difference while the eye isopen is:|4035−3514|+|3514−2813|+|2813−2542|+|2669−2542|+|2669−2645|+|2835−2645|=1834

Based on Equation (4), the brightness sum difference while the eye isclose is:|3772−3226|+|3226−2703|+|2703−2643|+|2878−2643|+|3365−2878|+|3745−3365|=2231

In view of above-mentioned examples, the brightness sum difference whilethe eye is close is larger than the brightness sum difference while theeye is open. That is, the brightness for a peripheral part for thedarkest part of the detecting image while the eye is close varies moresharply than the brightness for a peripheral part for the darkest partof the detecting image while the eye is open. Therefore, the brightnessvariation for a peripheral part for the darkest part of the detectingimage can be applied to determine if the user's is in an opening stateor in a closing state.

Please note although the pixel row is applied as an example to explainthe embodiment in FIG. 5, the pixel column can be applied to compute thebrightness variation tendency as well. Therefore, an eye state detectingmethod can be acquired based on the embodiment of FIG. 5, whichcomprises the steps illustrated in FIG. 6 as below:

Step 601

Capture a detecting image. Such step can apply the detecting range inFIG. 1 to capture the image, but not limited.

Step 603

Compute a brightness sum for a plurality of image lines of the detectingimage in a particular direction. For example, pixel rows or pixelcolumns.

Step 605

Apply one of the image lines which has the brightness sum with a lowestvalue as a standard image line.

Step 607

Compute a brightness sum difference between the brightness sum of thestandard image line and brightness sums for at least two of the imagelines.

Step 609

Decide a brightness variation tendency according to the brightness sumdifference

Step 611

Determine whether a user's eye is in an opening state or in a closingstate according to the brightness variation tendency

Please note the above-mentioned steps 603-609 can be combined to form astep of “compute a brightness variation tendency for a peripheral partof a darkest part of the detecting image”. However, such step can beformed by other steps rather than steps 603-609.

FIG. 7 is a block diagram illustrating an image detecting apparatusaccording to one embodiment of the present invention. As illustrated inFIG. 7, the eye state detecting system 700 comprises a control unit 701,an image sensor 703 and a computing unit 705. The control unit 701 andthe computing unit 705 can be integrated to a single device. If the eyestate detecting system 700 implements the embodiment illustrated in FIG.1, the control unit 701 controls the image sensor 703 to capture adetecting image SI via a detecting range. The detecting range is definedaccording to a possible location of a user's eye, and is smaller than amaximum detecting range that the electronic apparatus can apply. Thecomputing unit 705 computes a brightness of the detecting image SI, anddetermines whether the user's eye is in an opening state or in a closingstate according to the detecting image SI.

If the eye state detecting system 700 applies the embodiment illustratedin FIG. 5, the control unit 701 controls the image sensor 703 to capturea detecting image SI via a detecting range. The computing unit 705computes a brightness variation tendency for a peripheral part of adarkest part of the detecting image SI, and determines whether theuser's eye is in an opening state or in a closing state according to thebrightness variation tendency.

Other operations for the eye state detecting system 700 are described inabove-mentioned embodiments, thus are omitted for brevity here.

The above-mentioned embodiments firstly decide a detecting rangeaccording to a possible location of a user's eye, and then determinewhether the user's eye is in an opening state or in a closing stateaccording to a brightness variation tendency of the image. In followingembodiments, the face range is firstly determined, and then a searchingrange on the face range is decided. After that, determine whether theuser's eye is in an opening state or in a closing state according to theimage in the determining range. Detail steps will be explained infollowing descriptions.

Please refer to FIG. 8, which is a schematic diagram illustrating an eyestate detecting method according to another embodiment of the presentinvention. As illustrated in FIG. 8, a determiner CL (or named aclassifier) is configured to process the detecting image SI captured bythe image sensor. Such determiner CL determines if the detecting imageSI comprises a face image based on a pre-set face image feature module.If the detecting image SI comprises a face image, a face range Fr isdefined in the detecting image SI. After that, a determining range CR isdefined in the face range Fr. In one embodiment, such determining rangeCR is smaller than the face range Fr (but can be equal to the face rangeFr). Next, the determiner CL computes whether the determining range CRcomprises an open eye image or a close eye image according to an openeye image feature module or a close eye image feature module.

The above-mentioned embodiment applies a smaller determining range CRand the computing for a whole image is not needed, such that thecomputing loading can be decreased. In one embodiment, if it isdetermined that the detecting image SI does not comprise a face image,the step for defining the determining range CR and the step forcomputing if the determining range CR comprises an open eye image or aclose eye image can be removed. By this way, the computing loading canbe further decreased. Various methods can be applied to define thedetermining range CR. In one embodiment (but not limited), a possiblelocation for the eye is determined, and then the determining range CR isdefined according to the possible location.

FIG. 9 is a schematic diagram illustrating detail steps for theembodiment illustrated in FIG. 8. In the step 901, a determining moduleis generated based on module building data. For example, at least oneimage comprising the face image can be provided to build the face imagefeature module as the determining module. Alternatively, at least oneimage comprising an open eye image is provided to build the open eyeimage feature module as the determining module. Similarly, at least oneimage comprising the close eye image can be provided to build the closeeye image feature module as the determining module. The step 903 isapplied to pre-process the module building data, for example, adjustingthe brightness or the contrast to make following steps easier. However,the step 903 is removed in another embodiment.

Also, the step 905 extracts features from the module building data, andthe step 907 builds the module corresponding to the features extractedin the step 905. For example, at least one image comprising the faceimage is input in the step 901. Also, the step 905 extracts features forthe face image, and the step 907 builds a face image feature modulecorresponding to the face image features extracted in the step 905. Bythis way, it can be known that which features should exist if an imagecomprises a face image. Besides, in the step 907, the detecting image tobe determined is input. The step 911 performs a pre-process similar withthe step 903. The step 913 extracts features from the detecting image.The step 915 determines if the detecting image comprises a face image,an open eye image or a close eye image according to which one of thedetermining modules do features of the detecting image meet. After that,it can be determined that if the detecting image comprises a face image,an open eye image or a close eye image.

Various conventional algorithms can be applied to perform the step 905or the step 913 to extract features of images, for example, the gaboralgorithm or the harr algorithm. Similarly, various conventionalalgorithms can be applied to determine which one of the determiningmodules does the detecting image meet (i.e. classify the detectingimage), for example, the adaboost algorithm. It will be appreciated thatthe present invention is not limited to above-mentioned algorithms.

The embodiments illustrated in FIG. 8 and FIG. 9 can be performed by theeye state detecting system 700 illustrated in FIG. 7. Asabove-mentioned, the eye state detecting system 700 comprises a controlunit 701, an image sensor 703 and a computing unit 705. The control unit701 and the computing unit 705 can be integrated to a single device. Ifthe eye state detecting system 700 performs the embodiments illustratedin FIG. 8 and FIG. 9, the control unit 701 controls the image sensor 703to capture a detecting image SI. The computing unit 705 determines thedetermining range (ex. CR in FIG. 8) in the detecting image SI utilizingthe embodiments illustrated in FIG. 8 or FIG. 9, and determines if thedetecting image SI comprises an open eye image or a close eye imageaccording to images in the determining range CR. After that, the user isaccordingly determined if his eye is in an opening state or a closingstate.

Based upon the embodiments illustrated in FIG. 8 and FIG. 9, the eyestate detecting method provided by the present invention can besummarized as FIG. 10, which comprises following steps:

Step 1001

Acquire a detecting image via the image sensor (ex. SI in FIG. 8).

Step 1003

Define a face range on the detecting image (ex. Fr in FIG. 8).

Step 1005

Define a determining range on the face range (ex. CR in FIG. 8).

Step 1007

Determine if the determining range comprises an open eye image or aclose eye image.

In one embodiment, the methods illustrated in FIG. 8-FIG. 10 are appliedto non-wearable electronic apparatus. For example, a hand held mobileapparatus such as a mobile phone or a tablet computer, or an electronicapparatus such as a laptop, which can be put on a flat, can beimplemented as the non-wearable electronic apparatus (but not limited).

In view of above-mentioned embodiments, the eye state for the user canbe determined without detail image features and without an image havinga large range, thus the issue for prior art that an image with a highresolution is needed for determining the eye state for the user and highpower consumption due to large computing loading can be solved.

Those skilled in the art will readily observe that numerousmodifications and alterations of the device and method may be made whileretaining the teachings of the invention. Accordingly, the abovedisclosure should be construed as limited only by the metes and boundsof the appended claims.

What is claimed is:
 1. An eye state detecting method, comprising: (a)capturing a detecting image; (b) computing a brightness variationtendency for a peripheral part of a darkest part of the detecting image;and (c) determining whether a user's eye is in an opening state or in aclosing state according to the brightness variation tendency.
 2. The eyestate detecting method of claim 1, wherein the step (b) furthercomprises: (b1) computing a brightness sum for a plurality of imagelines of the detecting image in a particular direction; (b2) applyingone of the image lines which has the brightness sum with a lowest valueas a standard image line; (b3) computing brightness sum differencesbetween the brightness sum of the standard image line and brightnesssums for at least two of the image lines; and (b4) deciding thebrightness variation tendency according to the brightness sumdifferences.
 3. The eye state detecting method of claim 2, wherein theimage lines are image rows.
 4. The eye state detecting method of claim2, wherein the standard image line is a N-th image line of the detectingimage; wherein the step (b3) computes brightness sum differences betweenthe brightness sum of the standard image line and brightness sums foreach one of image lines from a N+1-th image line to a N+K-th image lineof the detecting image, and computes brightness sum differences betweenthe brightness sum of the standard image line and brightness sums foreach one of image lines from a N−1-th image line to a N-K-th image lineof the detecting image; wherein the K is a positive integer larger orequaling to
 1. 5. An eye state detecting system, comprising: a controlcircuit; an image sensor, wherein the control circuit controls the imagesensor to capture a detecting image via a detecting range; and acomputing circuit, configured to compute a brightness variation tendencyfor a peripheral part of a darkest part of the detecting image, and todetermine whether the user's eye is in an opening state or in a closingstate according to the brightness variation tendency.
 6. The eye statedetecting system of claim 5, wherein the computing circuit performsfollowing steps to compute the brightness variation tendency: computinga brightness sum for a plurality of image lines of the detecting imagein a particular direction; applying one of the image lines which has thebrightness sum with a lowest value as a standard image line; computingbrightness sum differences between the brightness sum of the standardimage line and brightness sums for at least two of the image lines; anddeciding the brightness variation tendency according to the brightnesssum differences.
 7. The eye state detecting system of claim 6, whereinthe image lines are image rows.
 8. The eye state detecting system ofclaim 6, wherein the standard image line is a N-th image line of thedetecting image; wherein the computing circuit computes brightness sumdifferences between the brightness sum of the standard image line andbrightness sums for each one of image lines from a N+1-th image line toa N+K-th image line of the detecting image, and computes brightness sumdifferences between the brightness sum of the standard image line andbrightness sums for each one of image lines from a N-1-th image line toa N-K-th image line of the detecting image; wherein the K is a positiveinteger larger or equaling to
 1. 9. An eye state detecting method,applied to an electronic apparatus with an image sensor, comprising: (a)acquiring a detecting image via the image sensor; (b) defining a facerange on the detecting image; (c) defining a determining range on theface range; and (d) determining if the determining range comprises anopen eye image or a close eye image.
 10. The eye state detecting methodof claim 9, wherein the step (b) defines the face range according towhether the detecting image comprises face image features.
 11. The eyestate detecting method of claim 9, wherein the determining range equalsto the face range.
 12. The eye state detecting method of claim 9,wherein the determining range is smaller than the face range.
 13. Theeye state detecting method of claim 9, wherein the step(c) determines ifthe determining range comprises the open eye image or the close eyeimage according to whether the determining range comprises open eyeimage features or close eye image features.
 14. An eye state detectingsystem, comprising: a control circuit; an image sensor, wherein thecontrol circuit controls the image sensor to capture a detecting range;and a computing circuit, configured to define a face range on thedetecting image, to define a determining range on the face range, and todetermine if the determining range comprises an open eye image or aclose eye image.
 15. The eye state detecting system of claim 14, whereinthe computing circuit defines the face range according to if thedetecting image comprises face image features.
 16. The eye statedetecting system of claim 14, wherein the determining range equals tothe face range.
 17. The eye state detecting system of claim 14, whereinthe determining range is smaller than the face range.
 18. The eye statedetecting system of claim 14, wherein the computing circuit determinesif the determining range comprises the open eye image or the close eyeimage according to whether the determining range comprises open eyeimage features or close eye image features.